Nigeria has launched a research initiative exploring how artificial intelligence can improve mental health screening among people who speak Yoruba, Hausa and Nigerian Pidgin. Known as the GENSCORE Project, the initiative aims to develop screening tools that recognise how emotional distress is expressed across different Nigerian languages and cultural settings.
The project was launched in Ibadan on October 29, 2026. It is led by the Slum and Rural Health Initiative (SRHIN), in collaboration with Imperial College London, the University of Ibadan and the Federal Neuro-Psychiatric Hospital, Yaba. Wellcome supports the research.
Addressing language barriers in mental healthcare
Mental health screening tools often rely on standardised questions developed in English or other widely studied languages. However, people may describe depression and anxiety differently depending on their language, culture and everyday experiences. Expressions of emotional distress can include local phrases, physical descriptions and cultural references that do not translate directly into English.
This creates a challenge for screening systems that do not account for local ways of communicating psychological experiences. GENSCORE aims to address this gap by developing tools that reflect how Nigerians express and understand mental health concerns. The need is significant. According to the project's research partners, fewer than 250 psychiatrists serve Nigeria's population of more than 220 million people, leaving many people with limited access to specialist mental healthcare.
How the GENSCORE project will use AI
The project is developing a multilingual dataset and an AI language model called GENSCORE-LLM. It will also develop culturally adapted screening tools known as GenPHQ and GenGAD, designed to support the assessment of depression and anxiety.
The research will explore written and spoken responses, allowing the team to examine how language and voice-based information can contribute to screening. The aim is to create tools that better recognise local expressions of emotional distress and support frontline health workers in identifying people who may need further assessment.
The project plans to involve 990 participants across study locations in Lagos, Abuja and Oyo State. Its tools will undergo community and clinical validation, including assessment against established clinical interviews, before their effectiveness can be established.
Why human oversight matters
The use of AI in mental healthcare raises important questions about accuracy, privacy and professional responsibility. A system that misunderstands a person's language or cultural expression could overlook signs of distress or incorrectly identify a mental health concern.
For this reason, GENSCORE is intended to support healthcare professionals rather than replace them. Clinical assessment, appropriate referral and professional judgement remain essential, particularly when dealing with sensitive mental health information. The collection and use of personal health data also require safeguards. Informed consent, confidentiality and responsible data management will be important to maintaining public trust in any tools developed through the project.
What it means for AI development in Africa
GENSCORE reflects a growing need for AI systems that account for African languages and local experiences. Much of the technology developed for global markets is trained on data that may not adequately represent the linguistic and cultural diversity of African populations. By focusing on Yoruba, Hausa and Nigerian Pidgin, the project is exploring how locally grounded research can make AI-supported healthcare tools more relevant to the communities they are intended to serve.
However, developing a multilingual AI model alone will not solve Nigeria's mental healthcare challenges. The availability of trained professionals, accessible health services and reliable referral systems will remain important to translating research into practical benefits. For now, GENSCORE is a research project, not a fully deployed diagnostic system. Its development and validation will determine whether AI can support more accessible and culturally relevant mental health screening in Nigeria.
